---
title: "AirBnb Dashboard"

output: 
  flexdashboard::flex_dashboard:
    source_code: embed
    vertical_layout: scroll
    theme: sandstone
    orientation: column

---






``` {js}
// Inverse color of navigation bar.
$('.navbar-inverse').removeClass('navbar-inverse').addClass('navbar-default');
```

```{r setup, include=FALSE}
library(flexdashboard)
library(tidyverse) # metapackage with lots of helpful functions
library(caret)
library(highcharter)
library(ggmap)
library(leaflet)
library(plotly)
library(listviewer)
library(ggplot2)
library(DT)
library(shiny)
Airbnbdata <- read_csv("AB_NYC_2019.csv")
```


```{r, include=FALSE}
df<-na.omit(Airbnbdata)
df <- Airbnbdata %>% mutate(avg_price = price/minimum_nights)
```

Overview
=======================================================================

 Column {.tabset .tabset-fade data-width=700 .colored }
-----------------------------------------------------------------------

### Location
```{r, fig.height=7}
leaflet(df %>% select(longitude,neighbourhood_group,neighbourhood,latitude,price)) %>%
  setView(lng = -73.95, lat = 40.73,zoom = 10) %>%
   addTiles() %>% 
  addMarkers(
  clusterOptions = markerClusterOptions())
```

Column {data-width=300}
-----------------------------------------------------------------------

### Number of hotel
```{r, fig.height=0.25}
valueBox(nrow(df), icon = "fa-ship", color="rgb(100,100,100)")
```

### Average price per day
```{r, fig.height=0.25}
valueBox(round(mean(df$price, na.rm = T),0), icon = "fa-heart", color="rgb(200,100,100)")
```


### Price by neighbourhood group
```{r,fig.height=2}
ggplotly(
  df %>% 
    filter(!(abs(avg_price - median(avg_price)) > 2*sd(avg_price))) %>%
    ggplot(aes(neighbourhood_group, avg_price, fill = neighbourhood_group)) +
    geom_boxplot() + 
    labs(title = "Average price by neighbourhood group",
         x = "neighbourhood", y = "average price per day ($)") +
    theme_classic() + theme(legend.position = "none")
)
```


### Price by room type
```{r,fig.height=2}
ggplotly(
  df %>% 
    filter(!(abs(avg_price - median(avg_price)) > 2*sd(avg_price))) %>%
    ggplot(aes(room_type, avg_price, fill = room_type)) +
    geom_boxplot() + 
    labs(title = "Average price by room type",
         x = "room type", y = "average price per day ($)") +
    theme_classic() + theme(legend.position = "none")
)
```

Room type
=======================================================================

 Column {data-width=700 .colored }
-----------------------------------------------------------------------

### Average price per day of common room
```{r, fig.height=2.5}
hchart(df$avg_price[df$avg_price < 500], color = "lightcoral", name = "Price per day") %>%
  hc_title(text = "Average price of common room") %>%
  hc_add_theme(hc_theme_ffx())
```

### Average price per day of high-class room
```{r,fig.height=2.5}
hchart(df$avg_price[df$avg_price >= 500], color = "palevioletred", name = "Price per day") %>%
  hc_title(text = "Average price of high-class room") %>%
  hc_add_theme(hc_theme_ffx())
```

Column {data-width=300}
-----------------------------------------------------------------------

### Number of common rooms
```{r,fig.height=0.25}
valueBox(nrow(df %>% 
                filter(avg_price < 500)), icon = "fa-heart",color="#B71C1C")
```


### Average price per day of common rooms
```{r, fig.height=0.25}
valueBox(round(mean(df$avg_price[df$avg_price < 500]),0), icon = "fa-heart",color="#B71C1C")
```

### Number of high-class room
```{r, fig.height=0.25}
valueBox(nrow(df %>% 
                filter(avg_price >= 500)), icon = "fa-heart",color="#006699")
```

### Average price per day of high-class rooms
```{r, fig.height=0.25}
valueBox(round(mean(df$avg_price[df$avg_price >= 500]),0), icon = "fa-heart",color="#006699")
```

### Availability
```{r, fig.height=3}
df1<- df %>%
  filter(availability_365 !=0)
hchart(df1$availability_365, breaks = 30, color = "salmon", name = "Availability") %>%
  hc_title(text = "Overall room availability") %>%
  hc_add_theme(hc_theme_ffx())
```

Animated Neighbourhood Graphs
=======================================================================

 Column {data-width=500 .colored }
-----------------------------------------------------------------------

### Price Variation in NYC Boroughs over Number of Reviews

```{r, fig.height=6}
upper.limit <- quantile(df$price)[4] + 2.5*IQR(df$price)
lower.limit <- quantile(df$price)[2] - 0.5*IQR(df$price)

bp_apt<-ggplot(df,aes(x=neighbourhood_group,y=price, fill=neighbourhood_group)) +
  labs(x="Neighbourhood Group", y="Price") +
  geom_boxplot(aes(frame= number_of_reviews))+coord_cartesian(ylim=c(lower.limit, upper.limit))+
  theme(axis.title.x = element_text(face="bold", size=14)) +
  theme(axis.title.y = element_text(face="bold", size=14)) +
  theme(legend.title = element_blank())

bp_apt <- bp_apt %>% animation_opts(
  1000, easing = "elastic", redraw = FALSE
)

bp_apt <- bp_apt  %>% animation_slider(
  currentvalue = list(prefix = "Number of Reviews ", font = list(color="cyan2"))
)


ggplotly(bp_apt)

```

Column {data-width=500 .colored }
-----------------------------------------------------------------------
### Plotly Aggregations of Price for Different NYC Boroughs

```{r, fig.height=6}

s <- schema()
agg <- s$transforms$aggregate$attributes$aggregations$items$aggregation$func$values


l = list()
for (i in 1:length(agg)) {
  ll = list(method = "restyle",
            args = list('transforms[0].aggregations[0].func', agg[i]),
            label = agg[i]) 
  l[[i]] = ll
}

anim <- plot_ly(
  type = 'bar',
  x = df$neighbourhood_group,
  y = df$price,
  mode = 'markers',
  marker = list(size = 12,color = 'cyan2'),
  transforms = list(
    list(
      type = 'aggregate',
      groups = df$neighbourhood_group,
      aggregations = list(
        list(
          target = 'y', func = 'avg', enabled = T)))))
anim <- anim %>% layout(xaxis = list(title = 'Neighbour Group'),
  yaxis = list(title = 'Price ($)'),
  updatemenus = list(list(
      x = 1.0,
      y = 1.0,
      xref = 'paper',
      yref = 'paper',
      yanchor = 'top',
      buttons = l
    )))
anim

```